The dynamics of R&D communities : implications for technology strategy

WORKING

PAPER

ALFRED

P.

SLOAN

SCHOOL

OF

MANAGEMENT

fir

Tfc]^

I

JUN

101989

June, 1989

THE

DYNAMICS

OF

R5D COMMUNITIES:

IMPLICATIONS

FOR

TECHNOLOGY STRATEGY

by

Michael

A.

Rappa

WP^

3023-89-BPS

MASSACHUSETTS

INSTITUTE

OF

TECHNOLOGY

50

MEMORIAL

DRIVE

CAMBRIDGE,

MASSACHUSETTS

02139

THE

DYNAMICS

OF

R^D COMMUNITIES:

IMPLICATIONS

FOR

TECHNOLOGY STRATEGY

by

Michael

A.

Rappa

THE DYNAMICS

OF

R&D

COMMUNITIES:

IMPLICATIONS FOR

TECHNOLOGY

STRATEGY

by

MichaelA.

Rappa

Assistant Professor of

Management

M.I.T.

Presented atthe

CORSATIMS/ORSA

Conference

May

8, 1989, Vancouver,

Canada

Massachusetts InstituteofTechnology

Alfred P. Sloan School of

Management

50

Memorial

Drive,

E52-538

Cambridge, Massachusetts

02139

USA

INTRODUCTION

A

central taskofthe research laboratory

manager

istodetermine theoptimal

allocation of scarce resources

among

a variety of technologies that could be

developed by theresearch staff. It is adifficultand unrelenting challenge with

no

clearanswers and with the optionschanging overtime.

Whether

itis a promising

new

technology on the horizon or a technology currently in

development

that is

proving less promisingthan initially thought, the laboratory's ix)rtfolioofprojects

issubject tofrequentreview and reconsideration.

In

what

directions should a research laboratory

expend

its effon?

What

new

technologiesshould be vigorously pursued, and

what

existing projects should

be curtailed? In sorting through these questions, the laboratory

manager must

assess each technology's potential impact on current business, itsrisks, its return,

and estimate the length of time it might take toreach the marketplace—all with an

eye toward

what

might be

done

by competitors.

The

time frame or

window

for a technology isparticularlycritical to the assessment.

Even

though the potential ofa technology

may

seem

significant, its importance will increase or diminish depending

upon

the lengthof time itwill take todevelop.

There

is

no

easy formula forestimating a technology's

window.

Over

the past several decades theeffort todevelop the field of technological forecasting has

yielded a limited

number

ofapproaches, but even so

most

firms continue to rely

heavilyon

expen

judgement.'

The

benefits and limitationsof

expen judgement

are

fairly well understood: in short, experts in a given technology are the

most

knowledgeable tojudge it, butthey are

more

likely tooverestimate itspotential and

'Sec for example. Fusfeld and Spilal. 'Technology Foreca5ling and Planning in the Coqxsraie Environment," 1980, and Mariin and Irvine, Foresighi in Science, 1985.

underestimatethe degree ofdifficulty in bringing itto fruition.2 Moreover, itisnot

unusual to find that foreveryoptimistic opinion an equally pessimisticone can be

found.

Given

that resources are limited, thedetermination over the worthiness of

developing a particular technology

may

place a laboratory's researchers at odds with

one

anotherand the resulting debate can reach an impasse. This can

make

laboratory life interesting forone

who

enjoys hearty exchanges, but itis

no

solace

for the

manager

who

needs to take action and

make

effective allocation decisions.

Indeed, the entire laboratory atmosphere can

become

strained,

when

researchers

become

impatient with the slowness in approving

new

projects and

managers

become

impatient waiting for investments in

ongoing

projects to yield tangible

products or processes.

The

discovery of superconductivity at high temperatures in bulk ceramic

materials (namely, the

compound

of lanthanum-barium-copper-oxide) in

1986

servesas a excellent

example

ofthechallenge posed by an

emerging

technology.

3

The

event,

which

occurred at the

IBM

research laboratory in Zurich, Switzerland

by two

scientists

who

later

were

awarded

a

Nobel

FYize for their effort, is

considered today to be extremely significant in terms of both its scientific and

technological implications and indeed,

some

believe

on

the

same

scale as the

discovery of the transistor effect in semiconductor material at Bell Laboratories

forty yearsago. Likethe transistor,itcould ultimately lead tovastimprovements in

areas such as high-speedcomputing.

However,

the realization ofa

computer

with

components

based upon the

new

superconducting material is not atrivial task noris

itcertain whetherit could be achieved-let alone when. Several problems will have

to be addressed, such as, refining the crystalline structure of the material,

improvingits electrical characteristics, fabricatingitintouseful devicesand circuits

in high volume, packaging thecomponents, integrating these

components

into the

otherpartsofthe system, and resolving the scientific question of

why

the materials

behave astheydo.

^See Anderson,Long-Pange Forecasting, Chapter 6,for adiscussionofjudgmental methods. Also see Luukkonen-Gronow, "Scientific Research Evaluation," 1987, forareview ofqualitativeand

quantitative methods.

^See Muller and Bednorz,"The DiscoveryofHigh-TemperarureSuperconductors," 1987, and Foner andOrlando, "Superconductors; The Long Road Ahead," 1988.

The

anticipated speed in

overcoming

theobstaclesfacing theapplication of

superconducting ceramics can

make

all the difference in deciding the proper allocation ofa laboratory'sresourcesovertime. Yet

judgments

aboutthe probable

time frame for the technology's

development

are

vague

at best and opinions are

often divided. Initially, rapid progress leading to

even

more

important

superconducting ceramic

compounds

(yttrium-barium-copper-oxide, inparticular) generated

widespread

enthusiasm

for near

term

commercialization of the

technology.

However,

the reality of

what

lies ahead

now

has givenrise to a

more

sober opinion

among

some

researchers about the long term nature ofthe effort.

TTie perils of this situation are readily apparent to the laboratory manager: ifone

accepts the opinion that such a

computer

can be realized within five years, the

appropriate allocationof resources willbe substantially different than ifone holds

the opinion that such a

computer

can be realized only within fifteen years. Ironically, it

was

the

same

firm,

IBM,

which

beginning in the early 1970's

attempted todevelop a superconducting

computer

(using

niobium

alloys), but had to scale back its effort in 1983 after reportedly spending as

much

as one-hundred

million dollars withoutsuccess.'^

The

case of superconducting ceramics is not unique. In thepast,

managers

have wrestled with similardecisions and they will continueto

do

so in the future.

5

Time

and again, they

must

grapple with the laboratory'sresearch agenda, seeking

to understand

what

new

technologies are gaining

momentum

and

what

ones are

grinding to a halt at the researcher's bench.

The

purpose of this study is to assist the research laboratory

manager

in

understanding the rate of progress in the

development

of technology in order to

improve

their effort to optimize resource allocation. Specifically, a theoretical

model

isproposed forassessing the developmentalrate of anemerging technology.

The

model

focuses on the

community

of researchers that coalesces around a

^See Robinson. "IBM Drops Superconducting Computer Project," 1983.

'Recent claims regarding "cold fusion," ifverified, may hold asimilar challenge as thatof high-temperature superconductors. See Pool, "Fusion Breakthrough?" 1989.

technology: that is, the scientists and engineers

who

are

committed

to solving an

interrelated set of scientific

and

technical problems,

and

who may

be

organizationally and geographically dispersed, but

who

nevertheless

communicate

witheachother.

The model

seeksto uncoverthe relationship betweenthe structural

and behavioral

dynamics

of this

"R&D

community"

and its rate ofprogress in

solving the

mjtiad

ofproblems it faces.

The

theory supports the contention that

certain changes in the structural and behavioral characteristics ofthe

community

may

berelated tothe acceleration or decelerationofatechnology'sprogress toward commercial introduction.

R&D

COVnv^UNTTIES

In his influential

work The

Limits of Organization,

Kenneth

Arrow

states

that "...organizations are a

means

of achieving the benefits ofcollective action in

situations

where

in

which

the price system fails." Following in a similar vein, it

may

be that

R&D

communities

are a

means

ofcollective action in situations in

which

the firm (or managerial hierarchy) fails.

Given

thisperspective, it

may

be

helpful to

view

such

communities

as efficient meta-organizational structuresfor accomplishing certain goals reasonably

beyond

the reach of the individual

researcheror team.

Despite the fact that the research

community

is a familiar concept in the

contextofthe scientificworld, itsplace in therealmoftechnological development is

largely

ambiguous.

^ It is well understood that scientists (particularly those

employed

in universityorgovernment) are

members

ofcommunities, the so-called invisible colleges, in

which

information flows with relative

freedom between

laboratories.

These communities

provide the

mechanism

by

which

members

mete

out recognition and rewards and set the direction for future research. In contrast,

technological

development

is typically seen as the

domain

ofengineers and the

*Thehistorian EdwardConstant, whose study ofthe developmentofthe turbojet elucidates the role ofthe technological community, stales: "While extensive research has been done on 'invisible colleges,'research fronts, and the community structureofscience, there has been little analogues sociological or historical investigation of technological practice." (Constant, 1980, p. 8.) For earlier studies of scientific communities see Griffilh and Mullins (1972) and Mullins (1972).

industrial firms that

employ

them. Firms operate to establish proprietary

know-how,

which

then can be leveraged to develop

new

products or processes that

surpass thoseofcompetitors. Secrecy, competition, and managerial direction are

the sine

qua non

of the technological landscape.

Given

this traditional

conceptualization of technological development, it appears that the notion of a

community

of researchersisatonce incongruent

A

closer examination of science and technology yields exceptions to such

broad stereotypes.

To

view

scientific

communities

as friendly clubs in

which

members

freely share their ideas is misleading.

Community

members

are not

immune

to fierce competition, racing to stake intellectual claims (typically in the

form

ofjournal articles, but increasingly in the

form

ofpatents'') and,even though

it

may

be contrary to established scientific norms, acting to restrict the flow of

information abouttheirresearch.

Likewise, the world oftechnology is equallyas complex. Firms compete,

but they also cooperate with each other, allowing technical information to flow

among

engineersin different organizations.8

Some

engineers attend conferences,

present technical papers, and publish the results of their

work

in peer-review

journals sponsored by professional societies. Like scientists, they too,

may

see

themselves as

members

ofa particular

R&D

community,

which extends

beyond

the boundary oftheir firm. Indeed,

some

are scientists, in that they are trained in the

scientific

method

and

may

havedoctoral degrees.

To

the extentthat researchers ina

particular technological

domain

consider themselves

members

of a

R&D

community,

this

community

may

play an instrumental role in influencing the rate

and direction of thetechnology's development. Contrary toestablished opinion, the

development

of a

new

technology

may

not simply the activity of a handful of

''Although ii is notnew, majorresearchuniversities, such asMITand Stanford, arepaying

increased aiteniion to opportunities to patent the inventions of faculty. MIT has a well-organized staff of professionals dedicated topatenting and licensing activities. See Eberlein (1989) for a description of

technology patenting and licensing activities atMIT. The importance of patenting is illustrated in the case of cold fusion research withMIT's recent announcement(viapress conference) that it applied for patents ona theoreticalexplanation of cold fusion, justone day after the theory was formulated (see

"Fusion in a Bottle," 1989).

'The flowof informationamong firmsisdocumented in the workof Allen (1979),andrecently ha.s received attention from von Hippcl (1987) in his examination ofknow-how trading.

engineers, or of a firm, but instead

many

individuals

working

in

numerous

organizations spread throughouttheworld.9

In the context of this study, the

R&D

community

is defined to include

individuals in any type oforganization, such as universities, private firms,

new

ventures, quasi-public corporations, and

government

research institutes, and

furthermore, the

community

can be global in scope. This concept of a

R&D

community

is obviously

more

inclusive than thatof an industry,but even

more

so

in that it includes firms with

no

regard to

what

industry they

may

be typically

classified (forexample, semiconductors, computers, chemicals, or aerospace) orno

matter what segmentthey

may

operate in (such aswith thesemiconductor industry,

there are

segments

dedicated to materials, devices, process equipment,

and

so

forth), so long as they are focusing

on

some

part ofthe relevant set ofproblems.

Thus, the

community

is defined

by

the

problem

set and not necessarily by the output, as isnormally thecase with anindustry definition.

THEORETICAL CONSIDERATIONS

Inreality, technological

development

is a vastly

complex

process. But for

this purpose it will be treated as a simplified theoretical abstraction. It is readily admitted that the theory does not adequately describe all of the subtleness of

technological

development

as it might actually occur.

However,

the intent is to

capture the essence ofthe process such that a basic understanding of the rate ofa

technology's

development

can be established.

The

foundation of the

model

rests on the principle that technological

development is an intellectual process

whereby knowledge

iscreated andappliedto

form

new

products orprocesses.

The

creation and application of

knowledge

entails

'Tlienotion ofa

R&D

community hasbeen obscured by the tendencyto viewtechnological

development in teirns of inventorsand their inventions, such as with the Shockley, Bardeen and

Brattain andthe transistor. However, acareful historicalaccount shows "It is...unrealistic to see the transistor as a product ofthree men,or ofonelaboratory,orof Physics, oreven ofthe forties. Rather its invention requiredthe contributions ofhundreds ofscientists, working in many different places, in

resolving certain

problems

which

stand in the

way

of realizing the desired

outcome.

10

_The

central actors are the individual researchers

who

become

committed

to solving the problems, and it is they

who

set the process in motion.

The

basicelementsofthe

model

areoutlined below.

(1) Let the

body

of

knowledge

in a given

realm

of technology be

represented as

K.

Given

the state of the world at the time of the technology's

initiation, the

body

of

knowledge

is projected as an increasing function over the

interval oft (0,«=) represented as K(t) in Figure 1(a).

Assume

that

K

can be

decomposed

into its constituent

pans

represented as k,

which

are

homogeneous

units of

knowledge,

where

K

=

Zk.

(2)

Given

K(t), letthe level ofproblems to be resolved (P) be an inversely

proportional function decreasing over the interval t {0,«»), represented as P(t) in

Figure 1(b).

Assume

that

P

also can be

decomposed

into its constituent parts,

which

are

homogeneous

units of problems,

where

P

= Zp.

The

relationship

between

the state of

knowledge

and the level ofproblems to be solved is given as

P(t)

=

u/K(t),

where

u isconstant.

At

time (t

=

1), given the assumptionsabout K(t)and P(t), a projection can

be

made

based onexpectations about the future point in time of commercialization

(tc), where the level of

knowledge

anained (Kc) is sufficient toreduce theproblems toa level (Pc) necessary to apply the technology to practice. Notice that it is not

assumed

all

problems

will be resolved, and, indeed, the

problem

solving activity continues after the technology's initial

market

entry. Furthermore, P(t) is

asymptotic to thex- and y-axis, implyingthat atthe initial stage (t --> 0),

P

is not ascertainable, and that as even as time progresses into the future (t —>°°),

some

problems

will never be satisfactorily resolved—it is the latter

which

gives rise to

new

technologies. It is also important to note that

even

given the initial

assumptions about K(t) and P(t), the probability of finding a solution to each

'OThe idea ihal technology is essentially knowledge has gained acceptance among scholars in

several disciplines. For example, see Arrow (1962), Layion (1974), Constant (1980), and Aitken

(1985). The work ofKalz and Allen (1985) focuseson technology development as aninformation processing and problem-solving activity. The intenthere is to link the concepts of information,

8

problem

is uncertain.

_n

Lastly, Ps (

=

P, - Pc) over the interval (t

>

c), will be

referred to as the

problem

set: a relatively large value of Ps implies a technology

which

isa radical departure

from

the established base of

knowledge

toreach tc. In

contrast,a relativelysmall value of Pj implies atechnology

which

is incrementalin

nature; that is, it is

more

an extension than a departure

from

existing base of knowledge.

(3) Let Ri (

= Xr)

represent the

community

of researchers

who

attemptto

createand apply

knowledge

in order toresolvetheproblemsfacing thetechnology

attime t.

Assume

they arerational, in the

economic

sense thatthey aremotivated

by

self-interest.

The

researcherconducts

two

basic activities: (a) the production

and

communication

of information, and (b) thetransformation of information into the

knowledge

required to solve problems. Information production implies the

creation of

new

data through observation and experiment.

Communication

of

information implies that the researcher can also gather information produced by

another researcher,

and

disseminate to others the information he produces.

Knowledge

is a distinct entity

from

information in that

knowledge

enables the researcher to

do something

(know-how)

or explain

something

(know-why).

Having

information does not necessarily imply either; the researcher first

must

make

sense oftheinformation availableto

him

inorderto solve problems.12

The

information production,

communication

and transformation processes

are time

consuming;

therefore, any individual researcher can only accomplish a certain level ofeffortin agiven period oftime.

Assume

that ina single period of

time, the

amount

ofinformation generated bya single researcher (r) is i, and that

he can perform

m

transformations.

The

information he produces and

how

he

chooses

to transform it into

knowledge

is an expression of the individual

researcher's

own

creativity, although he

may

be influenced

by

the people with

"Theconcept of uncertainty in technology development is developed by many authors, including Arrow(1962)who states "Producers [ofknowledge] havetomake decisionsoninputs at the piresent moment, butoutputs are notcompletelypredictable from the inputs."(p. 610) See also, Sahal (1983) who contends "We find...that technological fwogress is a cumulative process of learning to learn

andunlearn in aprobabilistic manner."(p. 216)

'^Theliterature on technological developmenttends totreat informationandknowledge as indistinguishable concepts. See, for example. Arrow (1962).

whom

he collaborates.

Not

aJl transformations aresuccessful in yielding a unitof

useful

knowledge.

Note

also,

any

given k might be obtained

from

different

transformations, or

from

the

same

transformation

implemented

simultaneously,

albeit independently, by different researchers.

The

probability that a particular

transformation will yield a unit of knowledge,

p(m)

=

k, cannot be determined a

priori, but rather is learned over time as researchers generate information and performtransformations. Moreover, the relevanceofany piece of information (in

that itmightform partofthe transformation which yields k) cannot be determined a

priori.

The

rate of growth in

knowledge

(3K/3t) is a function of the

number

of

diverse of transformations

(Zm)

that are performed, subject to the available

information

(Si)

and

the

amount

of additional

knowledge

required for commercialization

(Kz =

Kg

- K,): that is,

9K/3t

=

/(Xm

I Zi, K^). It is

expected that greater levelsin the diversityof

m

will be associatedwith higherrates

in the production of

new

unitsofknowledge. Moreover, the likelihood of success

of any given transformation improves as the

amount

of information it

draws

on

increases and as the

amount

of

knowledge

necessary for commercialization

decreases.13

The

research

community,

R, is said to be perfectly contiguous ifforeach r,

Xi]

= Xi2 =

Sis •••Zin; that is, information is symmetric. Conversely,

R

is

perfectly non-contiguous if for each r, Zii '^ _Ziz '' _Zis-.-Zini that is,

information is asymmetric.

The

degree of contiguity of

R

is influenced by the

existence of organizational boundaries

between

researchers and their

economic

motivations. Organizational boundaries areimportant for

two

reasons: first they

give rise toinformation asymmetries becausethey

impede

the flow ofinformation

and increase the cost of information gathering.

As

a result, organizational

boundaries can slow the rate ofproduction ofk within a

community

by reducing the

amount

of information available to each researcher.

However,

organizational

boundaries can also enhance therate ofk production to the extent it increases the

"This notion canbe understood interms ofKuhn's (1970) jig-saw puzzle analogy ofscience.

At the start, thepuzzle isquitedifficult,but as pieces are linked togetherand the picturebecomesmore

10

diversity of

m

pursued

by

R

as a whole, since researchers in different

organizations are likely to

have

different information sets and use different

transformations.

The

communication impedance

effect of organizational boundaries is

overcome

viaresearchers

who

act as technological gatekeepers--thatis,researchers

who

tend to

communicate

with others in different organizations.14

Given

the economically rational behavior ofresearchers, the

communication

ofinformation

across boundaries occurs as a

form

of quid pro

quo.n

Boundary-spanning

communication

is defined here ina restricted sense as person-to-p)erson exchanges and does not include publications. (Papers are very limited

mechanisms

for

information exchange becauseofthedelay in publication, theproblems in encoding

complex

information, and the inability toensure fairexchanges. Published papers

can serve as a

mechanism,

like patents,to stakeclaimstoknowledge.)

(4)

The

researcher's objective is to

maximize

the

number

of units of k he

produces and can lay claim to before otherresearchers.

Each knowledge

unit has

potential value, butit is

assumed

that the ultimate value ofthe researcher's claims

depends

upon whether

or not all

problems

necessary for reaching the point of commercialization are resolved and the length of time taken. That is,

knowledge

has value only

when

it is used, and the soonerit is used the greater value it will

have.

The

researcherdoes not need toproduce all the

knowledge

required toreach

to it is inconsequential to

him

who

solves theotherproblems, aslongashisclaims

toone or

more

k areestablished.

The

researcher's intellectual capital consists of

two

components: general

disciplinary

knowledge

that is held in

common

with other researchers, and

specialized

knowledge

that flows

from

his

work

related to a particulartechnology

(IM). It is

assumed

that the researcher can contribute to alternative technologies

within the realmofhisdisciplinary knowledge, and that he is free to switch atany

time.

1 1

Since hischoice isguided by theobjective to

maximize Zk,

theresearcher

is motivated to enter only those fields in

which

he believes the transformation

process has a high probability of yielding

him

units of

knowledge

he can claim.

The

value of

p(m)

=

k is learned over time as the

number

of transformations

researchers perform increases.

Thus

a researcher

may

be encouraged to enter a

field he believes might have a high value of p(m), but the actual probability can

only be determined with experience. If

p(m)

is equal to orgreater than expected

(i.e., the task of acquiring k is easier than anticipated), then the researcher will remain in the field; however, if/7(m) is lowerthan expected (i.e., acquiring k is

harder than anticipated), then the researcher might switch to another field with

higherperceivedp{m).

The

switching behavior ofaresearcherismoderated by the

length of time he spends contributing to a technology's

development

and the

amount

of

knowledge

claims he accumulates.

A

researcher's specialized

knowledge

(Zk)

becomes

a sunk cost: the

more

k theresearcheraccumulatesover time, thelesshkely he isto exita fieldpriortotc.

(5)

At

this point, it is possible to

draw

together the basicelements outlined

above

into a

dynamic model

of the process of technological

development

(see

Figure 2).i5

_To

_{begin, suppose} that at the initiation of a

new

technology (t

=

1),

there are a certain

number

of researchers involved (Ri)

who

in each instantoftime

produce a cenain

amount

ofinformation (Z'l) and perform a certain

number

of

transformations

(Xm).

The

researchers' effort yields a rate of

growth

in

knowledge

(3K/3t

>

0) which, given the

problem

set confronting them, implies a

rate of progress toward commercial introduction ofthe technology (5tm/3t,

where

tm

=

tc -1

1)-

The

resulting rate ofprogress, in turn, influences the decision of a

researcher to enter, remain in or leave the

community.

Since the size of the

research

community

determines

how much

information isproduced and

how many

transformations areperformed, theentryorexitdecision ofresearchers isofcritical

importance tothe acceleration or deceleration in the productionofknowledge.

Itis important tonotice that the researcher'sdecision toenterorexit a field

'^To be moreprecise, it may be possibletoformulate asystemsdynamic modelof

R&D

communities. Although not presented here, oneis currentlyunder consideration. See Roberts (1981)

12

is not a one-time choice, but rather is subject to consideration over time.

The

attractiveness ofdeveloping a particular technology changes over time, as

more

information is produced andresearcherslearn the probabilities in transforming this

information intoknowledge. Its attractiveness also

may

beinfluenced

by

changes

in other technologies, and indeed a variety ofother events, all of

which

will be

reflected inthe researcher's decision.

Suppose, as time progresses, the degree of difficulty in transforming

information into therequired

knowledge becomes more

apparent and it is lower

than expected. This will result in an acceleration in therate of

knowledge

growth

(32K/9t2

>

0) that implies a point ofcommercialization sooner than anticipated.

Some

researchers will respondtothischange inconditions byentering into thefield

(3R/8t

>

0),

which

will contribute to the production of information and

transformation process and feed the acceleration further. Conversely, suppose the

transformation process performed

by

researchers is proving

more

difficult than

expected. This will result in adeceleration in the growth of

knowledge

(32K/3t2

<

0) and,consequently, thepointof commercialization will be shifted furtherout into the future. This is a negative signal to potential entrants and

may

also lead to the

exit of researchers

from

the field (subject to their sunk cost considerations

mentioned above.)

The

effectsofthese changes areillustrated in Figure 3 and4.

The

impact oftheflow of researchersinto a field on

dKJdt

ismoderated by

the burgeoning

community's

structure and behavior: that is, the contiguityof the

community

as determined by the distribution ofresearchers across organizations

and the

communication

between them.

To

illustrate thispoint,

assume

theextreme

conditionsofperfectcontiguity and perfect non-contiguity. In the firstcase, as the

research

community

grows, all researchers are

employed by

the

same

organization.

Thus

all researchers are

assumed

tohave the

same

information set, but the diversity

oftransformationsperformed is limited by the researchers'mutual influence. Inthe

second case, as the

community

grows, each researcher is

employed

in a separate organization. Thus,each researcheris working from a different set ofinformation

and

performing

independent

transformations, such that the diversity of

transformations is maximized.

Simply

stated, in one situation each researcher in

13

transforming that information into knowledge; in theother situation, althoughthe

community

generates the

same amount

information, the

amount

available to any particularresearcheris small and the varietyof approaches takenis great

STRATEGIC

CONSIDERATIONS

Technology

strategy has tended to focus

on

the firm and industry as the

principal units of analysis. It is proposed here that the concept of an

R&D

community

may

have something to add to our understanding of technological

development,

and thus

may

prove

useful in the strategic considerations of managers. This section will review the possible benefitsof an

R&D

community

perspective totechnology strategy.

First, examination of the

R&D

community

broadens attention

from

the

analysisof firms in a panicular industry (as define by its products), toall typesof

organizations in various types ofindustries and sectorsofthe

economy.

This

more

comprehensive perspectivecan bemost critical in understanding the

emergence

ofa

new

technology, since a

whole

new

industry

may

form from

the efforts of these

disparate organizations.

For

example,

in the case of the

emergence

of

semiconductor technology, it lead tothe formation ofa

new

industry distinct

from

the industry

based

on

the established

technology

(that is,

vacuum

tube

manufacturers).16

Second, analysis of

R&D

communities

may

provide for betteranticipation of

emerging

technologies. It is typical for

emerging

technologies to be in

development

for a decade or

more

prior to commercialization. Therefore, the

evolution of the

R&D

community

can precede the formation of an identifiable

industry

by

many

years. Strict focus

on

the industry

may

lead to chroniclags in a

firm's technology developmentefforts.

Third, focusingon the

R&D

community

may

provide

managers

withinsight into the structure of the social network

among

researchers and

communication

14

flows.

The

evolvingnetwork structure

may

be an early signal to the formation of strategic alliances

between

firms as the technology approaches

commercial

introduction. Also, analysis of the network structure will enable the firm to

determine whetheror not it is adequately--as researchers say--"plugged-in to the

grapevine."

Where

a

fum

sitsin the network determines

how

much

infoimation is

available to its researchers. TTie firm does not have to be a central

node

in the

network, so long asit

knows

and interacts with those organizations

which

are the

central nodes.

Fourth, the

R&D

community

perspective highlights the collective action

dimension of technological development, and in this

way

it addressesdirectly the

strategic interdependence

which

may

arise. Unless a researcher or a firm can

produce

all the necessary information and resultant

knowledge

required for

commercialization ofatechnology, thenthe technology's developmentis ultimately

a collective action

problem

where

the decisions of researchers and firms are

interdependent.

Managers

can view themselves in a adversarial position,

where

the

objectis tomonopolizeclaims toall units of

knowledge

withrespecttoapanicular

technology; or

mangers

can seethemselves faced with a collective action problem,

in

which

the goal is toestablish

some

claims to

knowledge

while at the

same

time

promoting the technology's development

among

other organizations sothat all the

necessary

knowledge

will be established.

The

approach takenhas implications forthereturn, rate of development, and

risk facing the firm. In the first case, the return is relatively high, but the speedat

which

the technologydevelops

may

be slowerandthe riskofabsolute failure inthe

effort great. In comparison, in the second case the return

may

be lower, but the

rateofdevelopment fasterand theriskofabsolutefailureless.

The

well-known

historical

example

that illustrates this concept is the

development

ofsemiconductor technology beginning with thetransistor. Afterthe

invention of the point contact transistor at Bell Laboratories,

AT&T

pursued a

strategy to

promote development

of the technology broadly holding symposia to

transfer information and

knowledge

about the transistor to all other interested organizations, and offering low-royalty Hcenseson the transistorpatent.

The

effect

15

on the growth ofa semiconductor

R&D

community was

noticeable, as

many

more

organizations did

become

involved in developing the transistor. Indeed,

many

critical advancementsin semiconductortechnology necessaryforcommercialization

ofthe technology

came

from

researchers outside ofBell Laboratories, researchers

who

might not have taken part in the technology's

development

had it not been for

AT&Ts

promotional efforts.

CONCLUSION

This paper proposes the idea that the

"R&D

community"

is a usefulconcept

in understanding the rateofatechnology's development toward commercialization.

An

initial theoretical exposition is provided, and a brief discussion of the

implications for technology strategy. Clearly

much

more

research is required to

fully understand theimportanceofthis conception oftechnological development.

A

research

program

focused

on

the study of

R&D

communities

in

technological

development

iscurrently in progress. This research seeksto identify

and

measure

changes over time in the structural and behavioral characteristics of

R&D

communities

and the relationship

between

these factors and the rate of

progress achieved. Technologies underinvestigation include:

-GALLIUM

ARSENIDE INTEGRATED

dRCUTTS

-JOSEPHSON

JUNCTION

DEVICES

-REDUCED INSTRUCTION

SET

COMPUTERS

-IvTEURAL

NETWORK

COMPUTERS

-MAGNETIC

BUBBLE

MEMORY

STORAGE

DEVICES

-HIGH-TEMPERATURE

SUPERCONDUCTING

MATERIALS

-POLYPROPELENE PROCESS

TECHNOLOGY

-EPDM

RUBBER

PROCESS

TECHNOLOGY

-MICROGRAVITY MATERIALS PROCESSING

Although

these studies are already yielding a wealth of information about

R&D

communities, furtherresearch is required for insight into

why

R&D

communities

16

function as they

do

and toprovide better a understanding of the implications for

17

BreLIOGRAPHY

Allen,TJ.,Managing theFlowof Technology (Cambridge:

MIT

Press, 1977).

Annstrong,J.S.,Long-RangeForecasting,2ndEdition(New York:Wiley, 1985).

Arrow,K.J., "Economic Welfare andihe Allocation ofResources forInvention" in The Raleand Direction ofInventiveActivity,

NBER

(Princeton: PrincetonUniversityPress, 1962).

Arrow, Kenneth J.,TheLimitsofOrganization (New York: Norton, 1962).

Braun,E.andMacdonald,S., RevolutioninMiniature:The HistoryandImpact of Semiconductor

Electronics,2ndEdition(Cambridge,CambridgeUniversityPress, 1982).

Constant, E.W., The Origins ofthe Turbojet Revolution (Baltimore: Johns Hopkins University

Press, 1980).

Dasgupta,P. "Patents, Priority and Imitation or.The Economics ofRaces and Waiting Games," TheEconomicJournal 98 (1988): 66-80.

Dasgupta, P. and David, P. A., "Information Disclosure and the Economics of Science and Technology," in G. Feiwel (ed.). Arrow and the Ascent ofModern Economic Theory (New York:

NYU

Press, 1987).

Eberlein,J.A., "TechnologyTransferat MIT:

An

Analysis oftheTechnology LicensingOffice,"

S.M.Thesis,

MIT

(Cambridge,Massachusetts) 1989.

Foner, S. and Orlando, T.P., "Suf)erconductors: The Long Road Ahead," Technology Review,

(1988): 36-47.

Fusfeld, A.R. and Spital, F.C., "Technology Forecasting and Planning in the Corporate

Environment," in TIMSStudies in theManagementSciences, 15,(1980): 151-162.

"Fusionin a Bottle: Miracle orMistake?"BusinessWeek,(May 8, 1989): 100-110.

Griffith, B.C. and Mullins, N.C., "Coherent Social Groups in Scientific Change," Science, 177

(1972): 959-964.

Katz, R. and Allen, T.J., "Organizational Issues in the Introduction of

New

Technologies," in

P.R. Kleindorfer (ed.). The Management of Productivity and Technology in

Manufacturing (PlenumPress, 1985).

Kuhn, T.S. The Structure of TechnologicalRevolutions, 2nd Edition (Chicago: University of

Chicago Press, 1970).

Layton,E.T., "TechnologyasKnowledge," TechnologyandCulture 15 (1974): 31-41.

18

Mijllcr,K.A. and Bcdnorz,J.G.,"The Discovery ofHigh-Temperature Superconductors," Science,

237(1987;: 1133-39.

Mullins, N.C., "The Developmentofa Scientific Specialty,"Minerva 10 (1972): 51-82.

Pool.R.,"Fusion Breakthrough?" Science243 (1989): 1661-1662.

Roberts, E.B.,ManagerialApplicationsandSystemDynanvcs(Cambridge:

MIT

Press, 1981).

Robinson, A.L., "IBM Drops Superconducting Computer Project," Science. Ill (1983): 492-494.

Rogers, E.M., "Information Exchange and Technological Innovation," in D. Sahal, (ed.), The

TransferandViilizalion_ofTechnicalKnowledge(Lexington: Heath, 1982).

Sahal, D. "Invention, Innovation and EconomicEvolution," TechnologicalForecastingandSocial

C/w/igf23 (1983): 213-235.

Sahal, D. "Technological Progress and Policy," in D. Sahal (ed.),The Transferand Utilizationof

TechnicalKnowledge(Lexington: Heath, 1982).

von Hjpf)el,E.A., "Cooperation BetweenRivals: Informal

Know-How

Trading," ResearchPolicy

K

Kt Pc

FIGURE

1 (a) ic

FIGURE

2

KNONM-EDGE

INFORMATION

R.ATEOF

PROGRESS

LN

DEV'ELOPMENT

RESEARCH

COMMUNIPJ'

nCfRE

3 nGLTRF.4 Kt Pc Kt Pc IC t tc

Date

Due

NOV

13

US

JUN

119:}0

MIT LIBRARIES DUPl 1

3 TDflD

0DSb73T5

b